Changes in Leaf Area Index, Forage Quality and Above-Ground Biomass in Grazed and Ungrazed Rangelands of Eastern Anatolia Region

2009 ◽  
Vol 15 (3) ◽  
pp. 217-223 ◽  
Author(s):  
ERKOVAN H. Ibrahim;GULLAP
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Forage Quality ◽  
Eastern Anatolia ◽  
Above Ground Biomass ◽  
Area Index ◽  
Ground Biomass

scholarly journals Assessment of Leaf Area Index Models Using Harmonized Landsat and Sentinel-2 Surface Reflectance Data over a Semi-Arid Irrigated Landscape

2020 ◽  
Vol 12 (19) ◽  
pp. 3121
Author(s):  
Roya Mourad ◽  
Hadi Jaafar ◽  
Martha Anderson ◽  
Feng Gao
Keyword(s):  
Linear Regression ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Above Ground Biomass ◽  
Area Index ◽  
Ground Biomass ◽  
Semi Arid ◽  
Sentinel 2

Leaf area index (LAI) is an essential indicator of crop development and growth. For many agricultural applications, satellite-based LAI estimates at the farm-level often require near-daily imagery at medium to high spatial resolution. The combination of data from different ongoing satellite missions, Sentinel 2 (ESA) and Landsat 8 (NASA), provides this opportunity. In this study, we evaluated the leaf area index generated from three methods, namely, existing vegetation index (VI) relationships applied to Harmonized Landsat-8 and Sentinel-2 (HLS) surface reflectance produced by NASA, the SNAP biophysical model, and the THEIA L2A surface reflectance products from Sentinel-2. The intercomparison was conducted over the agricultural scheme in Bekaa (Lebanon) using a large set of in-field LAIs and other biophysical measurements collected in a wide variety of canopy structures during the 2018 and 2019 growing seasons. The major studied crops include herbs (e.g., cannabis: Cannabis sativa, mint: Mentha, and others), potato (Solanum tuberosum), and vegetables (e.g., bean: Phaseolus vulgaris, cabbage: Brassica oleracea, carrot: Daucus carota subsp. sativus, and others). Additionally, crop-specific height and above-ground biomass relationships with LAIs were investigated. Results show that of the empirical VI relationships tested, the EVI2-based HLS models statistically performed the best, specifically, the LAI models originally developed for wheat (RMSE:1.27), maize (RMSE:1.34), and row crops (RMSE:1.38). LAI derived through European Space Agency’s (ESA) Sentinel Application Platform (SNAP) biophysical processor underestimated LAI and provided less accurate estimates (RMSE of 1.72). Additionally, the S2 SeLI LAI algorithm (from SNAP biophysical processor) produced an acceptable accuracy level compared to HLS-EVI2 models (RMSE of 1.38) but with significant underestimation at high LAI values. Our findings show that the LAI-VI relationship, in general, is crop-specific with both linear and non-linear regression forms. Among the examined indices, EVI2 outperformed other vegetation indices when all crops were combined, and therefore it can be identified as an index that is best suited for a unified algorithm for crops in semi-arid irrigated regions with heterogeneous landscapes. Furthermore, our analysis shows that the observed height-LAI relationship is crop-specific and essentially linear with an R2 value of 0.82 for potato, 0.79 for wheat, and 0.50 for both cannabis and tobacco. The ability of the linear regression to estimate the fresh and dry above-ground biomass of potato from both observed height and LAI was reasonable, yielding R2: ~0.60.

scholarly journals Multifrequency and Full-Polarimetric SAR Assessment for Estimating Above Ground Biomass and Leaf Area Index in the Amazon Várzea Wetlands

2018 ◽  
Vol 10 (9) ◽  
pp. 1355 ◽  
Author(s):  
Luciana Pereira ◽  
Luiz Furtado ◽  
Evlyn Novo ◽  
Sidnei Sant’Anna ◽  
Veraldo Liesenberg ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Floodplain Forest ◽  
Single Frequency ◽  
Above Ground Biomass ◽  
Alos Palsar ◽  
Area Index ◽  
Ground Biomass ◽  
L Band ◽  
Sar Data

The aim of this study is to evaluate the potential of multifrequency and Full-polarimetric Synthetic Aperture Radar (SAR) data for retrieving both Above Ground Biomass (AGB) and Leaf Area Index (LAI) in the Amazon floodplain forest environment. Two specific questions were proposed: (a) Does multifrequency SAR data perform more efficiently than single-frequency data in estimating LAI and AGB of várzea forests?; and (b) Are quad-pol SAR data more efficient than single- and dual-pol SAR data in estimating LAI and AGB of várzea forest? To answer these questions, data from different sources (TerraSAR-X Multi Look Ground Range Detected (MGD), Radarsat-2 Standard Qual-Pol, advanced land observing satellite (ALOS)/ phased-arrayed L-band SAR (PALSAR-1). Fine-beam dual (FDB) and quad Polarimetric mode) were combined in 10 different scenarios to model both LAI and AGB. A R-platform routine was implemented to automatize the selection of the best regression models. Results indicated that ALOS/PALSAR variables provided the best estimates for both LAI and AGB. Single-frequency L-band data was more efficient than multifrequency SAR. PALSAR-FDB HV-dB provided the best LAI estimates during low-water season. The best AGB estimates at high-water season were obtained by PALSAR-1 quad-polarimetric data. The top three features for estimating AGB were proportion of volumetric scattering and both the first and second dominant phase difference between trihedral and dihedral scattering, extracted from Van Zyl and Touzi decomposition, respectively. The models selected for both AGB and LAI were parsimonious. The Root Mean Squared Error (RMSEcv), relative overall RMSEcv (%) and R2 value for LAI were 0.61%, 0.55% and 13%, respectively, and for AGB, they were 74.6 t·ha−1, 0.88% and 46%, respectively. These results indicate that L-band (ALOS/PALSAR-1) has a high potential to provide quantitative and spatial information about structural forest attributes in floodplain forest environments. This potential may be extended not only with PALSAR-2 data but also to forthcoming missions (e.g., NISAR, Global Ecosystems Dynamics Investigation Lidar (GEDI), BIOMASS, Tandem-L) for promoting wall-to-wall AGB mapping with a high level of accuracy in dense tropical forest regions worldwide.

Leaf Area Index and Above-Ground Biomass of terra firme Rain Forest and Adjacent Clearings in Amazonia

1993 ◽  
Vol 7 (3) ◽  
pp. 310 ◽  
Author(s):  
A.-L. C. McWilliam ◽  
J. M. Roberts ◽  
O. M. R. Cabral ◽  
M. V. B. R. Leitao ◽  
A. C. L. de Costa ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Rain Forest ◽  
Above Ground Biomass ◽  
Terra Firme ◽  
Area Index ◽  
Ground Biomass

scholarly journals (12) Influence of Single and Biculture Cover Crops with or without Synthetic Nitrogen on Leaf Area Index and Above Ground Biomass Yields of Sweet Corn

HortScience ◽  
2006 ◽  
Vol 41 (4) ◽  
pp. 1063B-1063
Author(s):  
Wayne F. Whitehead ◽  
Bharat P. Singh
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Cover Crops ◽  
Cover Crop ◽  
Sweet Corn ◽  
Dry Weight ◽  
Above Ground Biomass ◽  
Hairy Vetch ◽  
Area Index ◽  
Ground Biomass

During the 2004–05 growing season, a study was conducted to determine effect of cover crop, their mixture and fertilizer N rates on above ground biomass (AGB) yields, and Leaf Area Index (LAI) of Bt sweet corn. The following cover crop nitrogen fertility treatments were applied using randomized complete-block design with three replications: 1) fall-0 N, fallow; spring-0 N, 2) fall-0 N, abruzzi rye; spring-0 N, 3) fall-0 N, hairy vetch; spring-0 N, 4) fall-0 N, abruzzi rye+hairy vetch; spring-0 N, 5) fall-0 N, fallow; spring-101 kg N/ha, 6) fall-0 N, abruzzi rye; spring-101 kg N/ha, 7) fall-0 N, hairy vetch; spring-101 kg N/ha, 8) fall-0 N, abruzzi rye+hairy vetch; spring-101 kg N/ha, 9) fall-0 N, fallow; spring-202 kg N/ha, 10) fall-0 N, abruzzi rye; spring-202 kg N/ha, 11) fall-0 N, hairy vetch; spring-202 kg N/ha, and 12) fall-0 N, abruzzi rye+hairy vetch; spring-202 kg N/ha. In Spring 2005, `Attribute BSS0977' bi-color (BC) supersweet (sh2) corn seeds were field planted. AGB yields were collected during harvest week while LAI was recorded at tasseling (6/27), silking (7/8) and one week after harvest (7/25). Hairy vetch; spring-101 kg N/ha produced highest LAI at tasseling (2.18), silking (2.73), and one week after harvest (2.57). Lowest LAI at tasseling (1.12) and silking(1.60) were produced by abruzzi rye; spring-0 N with fallow; spring-0 N producing lowest LAI (1.40) one week after harvest. Maximum AGB fresh (40.5 Mg/ha) and dry weight (12.1 Mg/ha) yields were produced by hairy vetch; spring-101kg N/ha, while minimum AGB fresh (9.6 Mg/ha) and dry weight (3.6 Mg/ha) yields were produced by abruzzi rye; spring-0 N. Results imply LAI at each growth stage and AGB yields of this BCsh2 corn variety are best supported by hairy vetch supplemented with N at 101 kg/ha.

Above-Ground Dry Matter Production in Three Stands of Trembling Aspen

1972 ◽  
Vol 2 (1) ◽  
pp. 27-33 ◽  
Author(s):  
D. F. W. Pollard
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Matter ◽  
Dry Weight ◽  
Annual Production ◽  
Above Ground Biomass ◽  
Area Index ◽  
Mature Stand ◽  
Matter Production ◽  
Net Assimilation

Above-ground biomass, annual production, and leaf area index (LAI) were estimated for several years in aspen stands aged 6, 15, and 52 years old in 1968. Based on regressions of dry weight on stem diameter, biomass (stems and branches) estimates for 1968 were 21 500 kg ha−1 in the juvenile stand, 51 200 kg ha−1 in the intermediate stand, and 91 800 kg ha−1 in the mature stand. Net annual above-ground production (stems and branches) for these stands in 1968 was 6900, 7000, and 1340 kg ha−1 respectively. In 1969, foliage amounted to 2600, 2600, and 1500 kg ha−1, providing LAI of 2.4, 2.9, and 1.6 for the stands. Net assimilation rates were roughly 20, 17, and 9 g m−2 week−1.Aspen stands regenerated as suckers may attain maximum annual production within a few years, coincident with the development of maximum LAI.

scholarly journals Effects of drip irrigation on spring soybean (Glycine max (L.) Merr.) growth and soil physical indexes of Heilongjiang province of China

2019 ◽  
Vol 48 (1) ◽  
pp. 95-103
Author(s):  
Baoguo Zhu ◽  
Chunfeng Zheng ◽  
Huibin Jia ◽  
Qingying Meng ◽  
Nannan Wang ◽  
...  
Keyword(s):  
Glycine Max ◽  
Physical Properties ◽  
Leaf Area ◽  
Drip Irrigation ◽  
Growth Index ◽  
Soil Physical Properties ◽  
Above Ground Biomass ◽  
Area Index ◽  
Ground Biomass ◽  
Glycine Max L

Effects of different drip irrigation on the growth, development and yield of spring soybean was carried out by measuring the growth index and soil physical characteristics index of spring soybean (Glycine max (L.) Merr.). On the basis of natural precipitation in the same year, 4 drip irrigation levels, namely W1 (0 mm), W2 (200 mm), W3 (400 mm) and W4 (600 mm) were established. From flowering to the pod stage of soybean, a significant increase in the soil moisture and a reduction in the soil hardness and bulk density were observed. Though the difference between W3 and W4 was not significant, drip irrigation affected soil physical properties followed W4 > W3 > W2 > W1. Improved growth index including plant height, above-ground biomass and leaf area of soybean was also observed, but excessive drip irrigation triggered the decline of leaf area index and above-ground biomass. Changes caused in the soil physical properties due to drip irrigation affected soybean growth, which resulted a positive action on yield. Compared with W1 treatments, soybean yield in the different irrigation in the W3, W4 and W2 in the year 2015 and 2016 were increased by 83.68 and 46.99%, 61.58 and 39.47%, 23.51 and 20.21%, respectively. Based on the results of the present experiment it was observed that W3 treatment (irrigation rate 400 mm) was the best one for the improved crop yield of soybean.

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